Dataset Information

3D-QSAR and in-silico Studies of Natural Products and Related Derivatives as Monoamine Oxidase Inhibitors.

ABSTRACT: BACKGROUND:The computational development of human monoamine oxidase (MAO) inhibitors led to advancement in drug design and the treatment of many neurodegenerative diseases and neuropsychiatric disorders. The computational development of human monoamine oxidase (MAO) inhibitors led to advancement in drug design and the treatment of many neurodegenerative diseases and neuropsychiatric disorders. Different natural heterocyclic structures are reported to display selective MAO inhibitory activity by preclinical and in-silico modeling. OBJECTIVE:Currently, the major interest is devoted to the study of natural based therapeutic agents from the different categories. Therefore, we presenting the review to critically discuss and outline the recent advances in our knowledge on the importance of natural and natural based ligand-MAO insilico methods for novel MAO inhibitors. DISCUSSION:Several natural and related synthetic heterocyclic compounds such as coumarins, ?- carboline, piperine, naphthoquinone, morpholine, caffeine, amphetamine moreover flavonoids, chalcones, xanthones, curcumin are discussed for their MAO inhibitory profile along with molecular docking and quantitative structure-activity relationship studies. CONCLUSION:It is clear that, by this computational drug design approach, more particular, reversible and potent compounds can be proposed as MAO inhibitors by exact changes on the fundamental framework.

SUBMITTER: Dhiman P

PROVIDER: S-EPMC6080100 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

3D-QSAR and in-silico Studies of Natural Products and Related Derivatives as Monoamine Oxidase Inhibitors.

Dhiman Priyanka P Malik Neelam N Khatkar Anurag A

Current neuropharmacology 20180101 6

<h4>Background</h4>The computational development of human monoamine oxidase (MAO) inhibitors led to advancement in drug design and the treatment of many neurodegenerative diseases and neuropsychiatric disorders. The computational development of human monoamine oxidase (MAO) inhibitors led to advancement in drug design and the treatment of many neurodegenerative diseases and neuropsychiatric disorders. Different natural heterocyclic structures are reported to display selective MAO inhibitory acti ...[more]

PMID: 29189167

Similar Datasets

Project description:A strategy in the discovery of anti-tuberculosis (anti-TB) drug involves targeting the enzymes involved in the biosynthesis of Mycobacterium tuberculosis' (Mtb) cell wall. One of these enzymes is Galactofuranosyltransferase 2 (GlfT2) that catalyzes the elongation of the galactan chain of Mtb cell wall. Studies targeting GlfT2 have so far produced compounds showing minimal inhibitory activity. With the current challenge of designing potential GlfT2 inhibitors with high inhibition activity, computational methods such as molecular docking, receptor-ligand mapping, molecular dynamics, and Three-Dimensional-Quantitative Structure-Activity Relationship (3D-QSAR) were utilized to deduce the interactions of the reported compounds with the target enzyme and enabling the design of more potent GlfT2 inhibitors. Molecular docking studies showed that the synthesized compounds have binding energy values between -3.00 to -6.00 kcal mol-1. Two compounds, #27 and #31, have registered binding energy values of -8.32 ± 0.01, and -8.08 ± 0.01 kcal mol-1, respectively. These compounds were synthesized as UDP-Galactopyranose mutase (UGM) inhibitors and could possibly inhibit GlfT2. Interestingly, the analogs of the known disaccharide substrate, compounds #1-4, have binding energy range of -10.00 to -19.00 kcal mol-1. The synthesized and newly designed compounds were subjected to 3D-QSAR to further design compounds with effective interaction within the active site. Results showed improved binding energy from -6.00 to -8.00 kcal mol-1. A significant increase on the binding affinity was observed when modifying the aglycon part instead of the sugar moiety. Furthermore, these top hit compounds were subjected to in silico ADMETox evaluation. Compounds #31, #70, #71, #72, and #73 were found to pass the ADME evaluation and throughout the screening, only compound #31 passed the predicted toxicity evaluation. This work could pave the way in the design and synthesis of GlfT2 inhibitors through computer-aided drug design and can be used as an initial approach in identifying potential novel GlfT2 inhibitors with promising activity and low toxicity.

Dataset Information

3D-QSAR and in-silico Studies of Natural Products and Related Derivatives as Monoamine Oxidase Inhibitors.

Publications

3D-QSAR and in-silico Studies of Natural Products and Related Derivatives as Monoamine Oxidase Inhibitors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets